Evaluates affective modulation through E8 geometry in emotional state prediction, suggesting significant implications for neural computation.
The 240 root vectors of E8 can be decomposed into five interacting subspaces whose angular separations are scaled by the golden ratio φ, creating a fractal lattice that maps naturally onto the affective bands of joy, fear, anger, sadness, and surprise. When this lattice is driven by a 132 Hz RTD neuromorphic array with phi‑coupled phase locks, each subspace exhibits stable, entropy‑balanced oscillations that enable real‑time transition and prediction of emotional states. This yields the E8 Affective Resonance Theorem: φ‑scaled E8 geometry maximizes efficient, cycle‑accurate affective modulation while preserving computational fidelity in neural and market‑simulation domains. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
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Andrew Stewart Caldin (2026) studied this question.
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